In recent years, various hands-free human-computer interface paradigms have been developed as alternatives to the conventional graphical user interface (GUI) paradigms. One such paradigm implements a neurophysiological based communication system. With this system, neurophysiological brain activity sensors, such as electroencephalogram (EEG) sensors, are disposed on a person, and stimuli are supplied to the person. The EEG sensors are used to identify a particular stimulus supplied to the user. The supplied stimulus may, for example, correspond to a particular command. This command may be used to move a component of a robotic agent.
In addition to neurophysiological-based human-computer interfaces described above, various other neurophysiological-based systems have been developed that rely on real-time EEG-based sensing. These other systems may be used to, for example, monitor working memory, attention, and assist in target detection in image collections.
Although the neurophysiological-based systems described above present potential improvements over current technology paradigms, the systems that have been developed thus far have limited capabilities. This is due, in part, to the lack of system integrity verification to ensure the system is operating properly. More specifically, presently known neurophysiological-based systems do not implement any type of periodic or continuous monitoring capability verify that the system is operating properly. Rather, present neurophysiological-based systems employ checks of impedance and general electrical connectivity.
Hence, there is a need for a system and method that identifies whether the integrity of the system from the sensor connection through the signal processing chain is effective. In other words, that verifies that the system integrity is sufficiently sound to detect neural activity. The present invention addresses at least this need.